在合作式多微电网中进行多层技术经济环境能源管理优化,采用需求响应计划和不确定性考虑
Nehmedo Alamir1,2, Salah Kamel3, Tamer F Megahed4,5
1Electrical Power Engineering, Egypt-Japan University of Science and Technology, 21934, New Borg El-Arab City, Egypt. Nehmedo.alamir@aswu.edu.eg.
Scientific reports
|October 8, 2024
概括
本研究介绍了使用需求响应程序 (DRP) 进行合作的多层微电网 (MMG) 的多层优化模型. 该模型增强了技术经济环境能源管理,减少了排放,提高了可靠性.
科学领域:
- 能源系统工程 能源系统工程
- 优化理论 优化理论
- 环境科学 环境科学
背景情况:
- 微电网 (MMG) 需要复杂的能源管理,以平衡经济,环境和可靠性目标.
- 整合需求响应程序 (DRP) 为优化MMG运营提供了一条途径.
- 现有的优化模型经常与多目标复杂性和不确定性作斗争.
研究的目的:
- 为合作MMG能源管理开发一个多层,多目标 (MLMO) 优化模型.
- 同时优化运营成本,运营商利益,环境排放和MMG依赖.
- 解决可再生能源发电,负载需求和能源价格的不确定性.
主要方法:
- 为了客观处理,提出了一种新的混合 ε-词典学-加权总和方法.
- 实施了三层优化结构:1层用于DRP的经济调度,2层用于环境操作,3层用于可靠性最大化.
- 应用了增强平衡优化器 (EEO) 算法来解决MLMO问题.
- 使用2m+1点估计方法 (PEM) 来建模不确定性.
主要成果:
- 根据MLMO的方法,环境排放量减少了 (2.45%3.5%),独立性指数提高了 (2.49%4.8%).
- 案例研究证实了该模型在决定性和概率情景中的有效性.
- 概率模拟显示,平均成本略有增加 (约. 2.6%) 由于不确定性,验证了该方法的稳定性.
结论:
- 拟议的MLMO优化模型有效地平衡了合作MMG中的技术-经济-环境目标.
- 整合DRP和EEO算法为复杂的MMG能源管理提供了强大的解决方案.
- 该模型成功考虑了不确定性,提供了更高的可靠性和更少的环境影响.
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